[pymvpa] Using PLR with multiclass

[Neal Morton]

I have four classes, so I can’t just use {0,1}. It looks like no matter what the sample attributes of the input dataset are, MulticlassClassifier will send {-1,1} to the classifier. 

 

It looks like I need to either modify what MulticlassClassifier is sending to PLR, or change PLR to handle other labels.

 

 

From: Pkg-ExpPsy-PyMVPA <pkg-exppsy-pymvpa-bounces+mortonne=gmail.com at lists.alioth.debian.org> on behalf of Swaroop Guntupalli <swaroopgj at gmail.com>
Reply-To: Development and support of PyMVPA <pkg-exppsy-pymvpa at lists.alioth.debian.org>
Date: Wednesday, March 1, 2017 at 12:38 PM
To: Development and support of PyMVPA <pkg-exppsy-pymvpa at lists.alioth.debian.org>
Subject: Re: [pymvpa] Using PLR with multiclass

 

Does it help if you assign targets in your sample attributes to {0,1} instead?

 

On Wed, Mar 1, 2017 at 1:13 PM, Neal Morton <mortonne at gmail.com> wrote:

Is there a way to use PLR with a multiclass problem? When I try to use the MulticlassClassifier, that produces binary labels with -1 and 1. But PLR expects 0 and 1.

 

The classifier is created like so:

 

from mvpa2.clfs.plr import PLR

from mvpa2.clfs.meta import MulticlassClassifier

clf = MulticlassClassifier(PLR(lm=10))

 

When I try to train the classifier on an fMRI dataset with four classes, I get:

 

Traceback (most recent call last):

  File "/home1/03206/mortonne/analysis/bender/mvpa/loc_xval_diag.py", line 98, in <module>

    clf.train(ds1)

 File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py", line 137, in train

    self._train(ds)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py", line 1165, in _train

    CombinedClassifier._train(self, dataset)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py", line 628, in _train

    BoostedClassifier._train(self, dataset)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py", line 118, in _train

    clf.train(dataset)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py", line 137, in train

    self._train(ds)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py", line 1053, in _train

    self.clf.train(datasetselected)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py", line 137, in train

    self._train(ds)

  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/plr.py", line 76, in _train

    %(set(d),)

ValueError: Regressors for logistic regression should be [0,1]. Got set([1, -1])

 

 

I have the latest versions of meta.py and plr.py. There was a change in PLRWeights to support different values of labels, but that change doesn’t seem to have affected the PLR classifier.

 

Thanks,

Neal

 


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